Dates: Monday, January 25 - Friday, January 29, 2016

Session: 1:00pm - 4:00pm

Location: Sherrerd Hall 101

Instructor: Hubert Jin and Will Lowe

The Advanced Statistical Programming Camp builds on the Introductory Statistical Programming Camp by expanding the computing toolsets of researchers. The camp provides tools which can help analyze big datasets, e.g. voter files across many states, micro-level international trade data, large federal personnel databases, and employ computationally intensive methods, e.g. Monte Carlo simulations, Bayesian Markov chain Monte Carlo, cross-validation, or the bootstrap.

We begin by introducing some low-cost strategies for improving performance in R. To help process large data and improve the speed of computation, we then cover parallel execution of {R} code on both personal machines and on remote high performance computing systems available at Princeton. Lastly, we cover basic C++ and the use of Rcpp to produce tightly integrated and fast compiled code.

Please check the **Advanced Statistical Programming Camp** page for updates and more information.